D. Tsuru

664 citations
22 papers · 593 · h-index 9

Impact in

Papers in

    • Protein Hydrolysis and Bioactive Peptides 2
    • Chemical Synthesis and Analysis 2
    • Peptidase Inhibition and Analysis 5

D. Tsuru

21 papers receiving 561 citations

Peers

D. Tsuru
Comparison fields: 5 of 80
  • Oncology 272
  • Cellular and Molecular Neuroscience 130
  • Biotechnology 59
  • Cell Biology 88
  • Molecular Biology 353
Replace Eva Schirmer with:
Eva Schirmer Austria
Marija Abramić Croatia
János Seprődi Hungary
Anasua B. Kusari United States
Regine Koelsch Germany
Felicitas Lerner Germany
Nami Yabuki Japan
J Kraml Czechia
Emil Schiltz Germany
Xin Qi China
D. Tsuru relative to Eva Schirmer Austria Eva Schirmer's profile →
Citations per field
00.5×2×3×4×4.7×
Eva Schirmer · 1×
Citations per year

Countries citing papers authored by D. Tsuru

Since Specialization
Citations

This map shows the geographic impact of D. Tsuru's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by D. Tsuru with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Tsuru more than expected).

Fields of papers citing papers by D. Tsuru

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Tsuru. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by D. Tsuru. The network helps show where D. Tsuru may publish in the future.

Co-authors

The 25 scholars most cited alongside D. Tsuru, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with D. Tsuru Line = papers co-authored together D. Tsuru links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1980155
2 198897
3 199196
4 199168
5 199249
6 199440
7 199931
8 199910
9 197010
10 19926
11 19705
12
Modelling of Ignition and Combustion Characteristics of Heavy Residual Fuel Oil on Two Component Approximation
20094
13 20014
14 19984
15 19934
16 19993
17 20242
18
[Active site of acid proteases].
19892
19 20241
20
Understanding of combustion process in a premixed lean burn gas engine fueled with hydrogen enriched natural gas
20161

About D. Tsuru

D. Tsuru is a scholar working on Molecular Biology, Oncology, Biotechnology, Immunology and Materials Chemistry, having authored 22 papers that have together received 593 indexed citations. Recurring topics across this work include Peptidase Inhibition and Analysis (5 papers), Mast cells and histamine (4 papers), Enzyme Production and Characterization (4 papers), Protein Hydrolysis and Bioactive Peptides (2 papers), Phytase and its Applications (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Chemical Synthesis and Analysis (2 papers) and Hormonal Regulation and Hypertension (2 papers). The work is most often cited by research in Oncology (272 citations), Cellular and Molecular Neuroscience (130 citations), Biotechnology (59 citations), Cell Biology (88 citations) and Molecular Biology (353 citations). D. Tsuru has collaborated with scholars based in Japan and United States. Frequent co-authors include Tadashi Yoshimoto, Roderich Walter, Ana A. Kitazono, Hiroyuki Nagai, Kiyoshi Ito, A. Barth, Hiroshi Ōyama, Ilona Born, K. Neubert and P. Welker. Their work appears in journals such as Journal of Bacteriology, The Journal of Biochemistry, Structure, Photodiagnosis and Photodynamic Therapy and Pharmaceuticals.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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